---
title: Finetune a Model
sidebarTitle: Finetune a Model
---

## Description

The `FINETUNE` statement lets you retrain a model with additional training data.

<p align="center">
  <img src="https://docs.google.com/drawings/d/e/2PACX-1vTwrR36VeRCMQYZ7AMQXS1gzMtgv6URfIlKFTUqZiTSZwsuXjiZCi8tIr4yU7NBs3_IuGzKgelvQ8l9/pub?w=955&h=460" />
</p>

Imagine you have a model that was trained with a certain dataset. Now there is more training data available and you wish to retrain this model with a new dataset. The `FINETUNE` statement lets you partially retrain the model, so it takes less time and resources than the [`RETRAIN`](/sql/api/retrain) statement. In the machine learning literature, this is also referred to as *fine-tuning* a model.

## Syntax

Here is the syntax:

```sql
FINETUNE [MODEL] project_name.model_name
FROM integration_name
    (SELECT column_name, ... FROM table_name)
[USING
    key = value,
    ...];
```

Where:

| Expressions                                 | Description                                                                                                        |
| ------------------------------------------- | ------------------------------------------------------------------------------------------------------------------ |
| `project_name`                              | Name of the project where the model resides.                                                                       |
| `model_name`                                | Name of the model to be retrained.                                                                                 |
| `integration_name`                          | Name of the integration created using the [`CREATE DATABASE`](/sql/create/databases) statement or file upload.    |
| `(SELECT column_name, ... FROM table_name)` | Selecting additional data to be used for retraining.                                                               |
| `USING key = value`                         | Optional. The `USING` clause lets you pass multiple parameters to the `FINETUNE` statement.                          |

<Info>
**Model Versions**

Every time the model is finetuned or retrained, its new version is created with an incremented version number. Unless overridden, the most recent version becomes active when training completes.

You can query for all model versions like this:

```sql
SELECT *
FROM project_name.models_versions;
```

For more information on managing model versions, check out our docs [here](/sql/api/manage-models-versions).
</Info>

<Warning>
While the model is being generated and trained, it is not active. The model becomes active only after it completes generating and training.
</Warning>

## Examples 
### Example 1: [OpenAI Model Fine-Tuning](/finetune/openai)
### Example 2: [Llama2 Model Fine-Tuning](/finetune/anyscale)
### Example 3: [Regression Model Fine-Tuning](/finetune/regression)
### Example 4: [Classification Model Fine-Tuning](/finetune/classification)
